This paper presents a fuzzy basis function approach for adaptive decentralized control of a class of large-scale nonlinear systems with MEMO subsystems. Hybrid adaptive-robust tracking control schemes which are based on a combination of the IT∞ tracking theory, and fuzzy control design are developed such that all the states and signals are bounded and the H∞ tracking control performance is guaranteed. In addition, each subsystem is able to adaptively compensate for disturbances and interconnections with unknown bounds. The resultant decentralized control with multi-controller architecture guarantee stability and convergence of the output errors to zero asymptotically, by local output-feedback. Simulation results on the control of a model of a nonlinear electrical machine are presented to illustrate the effectiveness of the proposed controller.